1. Field of the Invention
The invention relates to the field of content delivery over a network. Specifically, in one exemplary aspect, the invention relates to methods and apparatus for selecting content from a variety of sources in a cable television or satellite network to a client device.
2. Description of Related Technology
Recent advances in content delivery technologies have led to the proliferation of different content sources carrying a wide variety of content. A viewer may be easily overwhelmed by the presentation of hundreds of broadcast channels, purchasable content channels (e.g., VOD, pay-per-view, etc.) and the like, offering programming 24 hours per day. A channel-by-channel search for specific content can be tedious and frustrating to the user. With such an abundance of content offered, the user may be unable to rapidly and easily locate content of interest at any one time.
Likewise, other technological advancements have brought into common use electronic devices that allow users to record content received from a bearer network (such as a cable television or satellite network), whether at their premises or another location within the network. These devices include, inter alia, on digital video recorders (DVR), and personal video recorders (PVR). Access to content stored on recording devices further increases the overabundance of content available to the user.
Some existing methods for specifically providing content in which a user may be interested, from among the large quantity and variety of content available, include the utilization of demographic data and/or explicit viewer designation of particular content. For instance, a user may have his/her content pre-selected (or at least the possibilities narrowed) based on their demographics, and/or explicit selections or preferences of the user. However, these methods generate targeted content based only on the information a user specifically gives or enters into the system (or which can be gleaned from their subscriber account, etc.).
Various other solutions have been presented to assist a user in finding content of interest including, for example, the utilization of computer programs adapted to generate “playlists” of recommended content. These programs rely on various filtering algorithms known in the prior art.
Filtering algorithms may generally be distinguished as being of one of two types; (i) those using collaborative filtering, and (ii) those which use content-based filtering. Collaborative filtering collects user data in the form of e.g., user-supplied ratings of individual pieces of content in a given domain. The similarities and differences of several user profiles are then examined to make a recommendation or decision for a piece of content. Collaborative filtering requires a community-based database. Alternatively, content-based filtering identifies items based on some correlation between characteristics in a piece of content and a user's preferences (or user's profile). However, the majority of these systems rely heavily on user-supplied criteria (“seed” items), and/or are static in nature (i.e., do not change unless the user changes the input criteria). Hybrid content-based and collaborative filtering systems have also been developed.
Alternative methods adapted to generate playlists of recommended content update themselves based upon a user's explicit feedback and/or a user's implicit actions. However, these methods cause the playlists generated to quickly become too narrowed and specific, and do not account for changes in a user's preferences over short periods of time, such as, within different parts of a day. Other prior art content-based systems recommend content based on a user profile, which is entered substantially by the user.
Various other solutions have also been presented to assist a user in finding content of interest including, for example, the utilization of a searchable program guide such as that described in U.S. Pat. No. 7,228,556 to Beach, et al., issued Jun. 5, 2007 and entitled “Distributed, Interactive Television Program Guide; System and Method”
Customizable program guides are also used in the prior art to provide targeted content to a user. These generally fit into two distinct categories: (i) those in which a user must enter preference data, and (ii) those that are able to gather data about a user without user specification. The first category of customizable program guides, as stated, inconveniently require a user to manually enter preference or other data. One example of the first category of customizable program guides is described in U.S. Pat. No. 7,185,355 to Ellis, et al., issued Feb. 27, 2007 and entitled “Program Guide System with Preference Profiles”. Exemplary prior art of the second category of customizable program guides includes U.S. Pat. No. 7,020,652 to Matz, et al., issued Mar. 28, 2006 and entitled “System and Method for Customizing Content-Access Lists”.
Based on the foregoing, there is a need for improved apparatus and methods for recommending or providing content that a particular user (or group of users) is most likely to have an interest in or find enjoyable, without undue burden on the user in terms of required inputs or feedback. Such apparatus and methods would not rely substantially on user-supplied criteria or ratings, and would also be adapted to dynamically and rapidly update to reflect a user's preferences with a high level of proficiency; the ability to update including the utilization of explicit and implicit data.
Such apparatus and methods would also generate profiles that would not become too narrowed over time, but rather would respond to a user's changing preferences including preference changes over short periods of time (such as during different parts of a day).
Additionally, the abovementioned apparatus and methods would provide a user with the ability to choose among recommended content, and present a user with a navigable list of content prioritized according to a system which immediately takes into account the users activities and thereby derives an even more finely tuned profile without becoming overly narrow and accounting for changes in a user's preferences over short periods of time, such as, within different parts of a day.
These features would also be provided using substantially extant network infrastructure and components, and would be compatible with a number of different client device and delivery systems including both wired and wireless technologies.